A novel strategy for predicting the performance of open vertical refrigerated display cabinets based on the MTF model and ASVM algorithm

被引:10
|
作者
Cao, Zhikun [1 ]
Gu, Bo [1 ]
Mills, Graham [2 ]
Han, Hua [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Mech Engn, Inst Refrigerat & Cryogen, Shanghai 200240, Peoples R China
[2] Environ Australia Pty Ltd, Sydney, NSW 2060, Australia
来源
INTERNATIONAL JOURNAL OF REFRIGERATION-REVUE INTERNATIONALE DU FROID | 2010年 / 33卷 / 07期
关键词
Display cabinet; Open cabinet; Prediction; Modelling; Flow; Air; Leakage; Simulation; 2-FLUID MODEL; FROST GROWTH; TURBULENCE; TEMPERATURE; FLOW; SIMULATION; DIAGNOSIS; HUMIDITY;
D O I
10.1016/j.ijrefrig.2010.04.006
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a novel strategy for predicting the performance of open vertical refrigerated display cabinets which is based on a modified two-fluid (MTF) model and an adaptive support vector machine (ASVM) algorithm. A MTF model (physical model) was built for open vertical refrigerated display cabinets, and then an ASVM algorithm (machine learning algorithm) was built. To verify the quantity of air leakage from the cabinet during operation, an important performance factor of display cabinets, an MTF model was built. After the training and validation data sets were constructed from the output of the MTF model, the problem was solved using an ASVM algorithm. The defrosting water quantity and total energy consumption / total display area (TEC/TDA), achieved from the experiments by using the predicted combination of the controlled parameters, were found to be reduced by 39.2% and 19.3%, respectively, from the experimental results of the original display cabinet. (c) 2010 Elsevier Ltd and IIR. All rights reserved.
引用
收藏
页码:1413 / 1424
页数:12
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